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Archive for the ‘economics’ category: Page 143

Aug 3, 2018

Scientists present concept for the elimination of traffic jams

Posted by in categories: economics, sustainability, transportation

A team of researchers from Cologne and New York has presented proposals for future traffic management. A dynamic, fair toll for road use could reduce congestion.

In the current issue of Nature, the economists Peter Cramton, Axel Ockenfels (both University of Cologne) and Richard Geddes (Cornell University) describe a concept in which drivers would have to pay a dynamic fee for the use of roads. This would contribute to avoiding traffic jams and protecting the environment, the researchers argue. Fees that respond to traffic volumes in and with site precision, taking into account factors such as vehicle type and exhaust emissions, can significantly improve and contribute to reducing air pollution.

Traffic jams are not only annoying and time-consuming, they are also costly. In Germany, the economic damage caused by congested roads in 2017 totaled approximately €80 billion. “Currently, who cause , while damaging the environment and even incurring costs, are paying just as much as those who are not involved,” says Ockenfels. “Without a toll, this means that the general public is subsidizing these users. That’s unfair.” A toll for road use would bring these costs to light and reduce congestion. “If the fee adapts to the volume of traffic and the situation on the road in real time, i.e., is more expensive at rush hour than around noon, everyone can choose the route that suits them best. This already works for navigation systems,” explains Cramton. “Ultimately, this would reduce the load on main traffic arteries, improve traffic flow and reduce CO2 emissions.

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Jul 31, 2018

Is Bitcoin Erasing 300 years of Monetary Evolution?

Posted by in categories: bitcoin, cryptocurrencies, economics, finance, government, innovation

Today, economist and Nobel laureate, Paul Krugman, wrote in the New York Times, that Bitcoin is taking us back 300 years in monetary evolution. As a result, he predicts all sorts of bad things.

A significant basis for Mr. Krugman’s argument is that the US dollar has value because men with guns say it does.

Is Bitcoin erasing 300 years of monetary evolution?

Running with the metaphor that fundamental change to an economic mechanism represents ‘evolution’, I think a more accurate statement is that Bitcoin is not erasing the lessons of history. Rather, it is the current step in the evolution of money. Of course, with living species, evolution is a gradual process based on natural selection and adaptation. With Bitcoin, change is coming up in the rear view mirror at lightning speed.

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Jul 31, 2018

Yes, humans are depleting Earth’s resources, but ‘footprint’ estimates don’t tell the full story

Posted by in category: economics

Experts widely agree that human activities are harming the global environment. Since the Industrial Revolution, the world economy has grown dramatically. Overall this is a success story, since rising incomes have lifted millions of people out of poverty. But it has been fueled by population growth and increasing consumption of natural resources.

Rising demand to meet the needs of more than 7 billion people has transformed land use and generated unprecedented levels of pollution, affecting biodiversity, forests, wetlands, water bodies, soils and air quality.

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Jul 30, 2018

Research finds silicon-based, tandem photovoltaic modules can compete in solar market

Posted by in categories: business, economics, solar power, sustainability

New solar energy research from Arizona State University demonstrates that silicon-based, tandem photovoltaic modules, which convert sunlight to electricity with higher efficiency than present modules, will become increasingly attractive in the U.S.

A paper that explores the vs. enhanced efficiency of a new solar technology, titled “Techno-economic viability of silicon-based, tandem modules in the United States,” appears in Nature Energy this week. The paper is authored by ASU Fulton Schools of Engineering, Assistant Research Professor Zhengshan J. Yu, Graduate Student Joe V. Carpenter and Assistant Professor Zachary Holman.

The Department of Energy’s SunShot Initiative was launched in 2011 with a goal of making solar cost-competitive with conventional energy sources by 2020. The program attained its goal of $0.06 per kilowatt-hour three years early and a new target of $0.03 per kilowatt-hour by 2030 has been set. Increasing the efficiency of photovoltaic modules is one route to reducing the cost of the solar electricity to this new target. If reached, the goal is expected to triple the amount of solar installed in the U.S. in 2030 compared to the business-as-usual scenario.

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Jul 28, 2018

AI & Technology Taking Over White Collar Jobs

Posted by in categories: economics, employment, health, robotics/AI

This podcast is from my article called, The U.S. Economy is Built on a Foundation of Sand.

While many Economists, are saying that the U.S. economy looks great and has a forward momentum, I’m going to take a different tone. Not a pessimistic tone but a realistic view based upon facts and my futurist intuitive insight.

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Jul 28, 2018

Could We Use Space to Pay for a Universal Basic Income?

Posted by in categories: economics, government, robotics/AI, space

Universal basic income is a generous idea in principle, with clear benefits to society. However, the question of how to pay for it remains an enigma. While some propose taxation, others think we should use the booming space trade to benefit us all.

Universal basic income is the idea that every citizen should receive an amount of money from the government to meet their needs, regardless of age, race, gender, or even need. It has been billed as a solution to a variety of current and potential societal problems, including AI automation, poverty, and people losing the ability to allocate their own time.

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Jul 26, 2018

Ion Engine Startup Wants to Change the Economics of Earth Orbit

Posted by in categories: alien life, economics, engineering, finance, habitats, information science, law

For as long as she can remember, she’s puzzled over what’s out there. As a kid drifting off to sleep on a trampoline outside her family’s home near Portland, Ore., she would track the International Space Station. She remembers cobbling together a preteen version of the Drake Equation on those nights and realizing that the likelihood of intelligent alien life was something greater than zero. Star Trek marathons with her father catalyzed her cosmic thinking, as did her mother’s unexpected death when Bailey was 8. The house lost some of its order—some of its gravity—which led to more nights gazing skyward on the trampoline.

In college, Bailey got a hard-won paid internship at the now-merged aerospace giant Hamilton Sundstrand and joined a team repairing turbine engines. She hated it. “It was the opposite of pushing the envelope,” she says. “Nothing new ever went into that building. Nothing new ever left that building.”

By the time she set off to get a master’s degree in mechanical engineering at Duke University, the idea of logging 30 years at a place like Boeing Cor NASA had lost all appeal. She tried her hand at finance and later law, and was unlucky enough to excel at both. “I made it pretty far down that path, but then I thought, Wait, if I become a lawyer, then I’m a lawyer and that’s what I do,” she recalls. “What if I don’t want to do that on Tuesdays?”

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Jul 25, 2018

Big Tech is Throwing Money and Talent at Home Robots

Posted by in categories: economics, mobile phones, robotics/AI

That may be about to change. Behind the scenes, big tech companies are funding secret projects to develop robots. Amazon.com Inc. has been working on a robot version of its Echo voice-activated speaker for a while now and this year began throwing more money and people at the effort. Alphabet Inc. is also working on robots, and smartphone maker Huawei Technologies Inc. is building a model for the Chinese market that will teach kids to speak English.


Alphabet and Huawei join Amazon in the race to build androids, the first of which could debut by 2020.

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Jul 24, 2018

Ocean acidification a challenge for science, governments & communities

Posted by in categories: economics, science

A new IMAS-led paper published in the science journal Nature Climate Change has highlighted the challenges faced by scientists, governments and communities as rising levels of CO2 are absorbed by the world’s oceans.

Researchers have found that in recent centuries surface ocean pH has fallen ten times faster than in the past 300 million years and that impacts are being felt on ecosystems, economies and communities worldwide.

The economic cost to coral reefs, wild fisheries and aquaculture alone of the process known as Ocean Acidification is projected to reach more than US $300 billion per annum.

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Jul 23, 2018

The Digital Poorhouse

Posted by in categories: biotech/medical, economics, information science, robotics/AI, security

About the future death of explainability to understand AI thinking, the writing is on the wall…


These divergent approaches, one regulatory, the other deregulatory, follow the same pattern as antitrust enforcement, which faded in Washington and began flourishing in Brussels during the George W. Bush administration. But there is a convincing case that when it comes to overseeing the use and abuse of algorithms, neither the European nor the American approach has much to offer. Automated decision-making has revolutionized many sectors of the economy and it brings real gains to society. It also threatens privacy, autonomy, democratic practice, and ideals of social equality in ways we are only beginning to appreciate.

At the simplest level, an algorithm is a sequence of steps for solving a problem. The instructions for using a coffeemaker are an algorithm for converting inputs (grounds, filter, water) into an output (coffee). When people say they’re worried about the power of algorithms, however, they’re talking about the application of sophisticated, often opaque, software programs to enormous data sets. These programs employ advanced statistical methods and machine-learning techniques to pick out patterns and correlations, which they use to make predictions. The most advanced among them, including a subclass of machine-learning algorithms called “deep neural networks,” can infer complex, nonlinear relationships that they weren’t specifically programmed to find.

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